All objects whose temperatures are higher than absolute zero can generate infrared radiation. The higher the temperature is, the larger the radiated energy is, and a spectrum characteristic curve of a substance is unique. Spectral data collection is a method and technology that mainly research spectral data of a collected target scene or a region of interest (ROI). The technology is widely applied in the field of remote sensing, and provides a data basis for researching spectrum characteristics of various target backgrounds and further performing classification, monitoring and target detection and identification on a scene.
Infrared image-spectrum association refers to integrating an infrared image and an infrared spectrum to perform target detection, so as to increase types of detection range targets and improve target identification capability. Therefore, research and development on related spectrum imaging devices receive much more attention around the world. Currently, common image-spectrum detection devices are mostly multispectral scanners and Fourier transform infrared imaging spectrometers. The multispectral scanner is generally mounted in an aircraft, and a scanning mirror thereof rotates, so that a received instant field of view (FOV) moves in a direction perpendicular to a flight direction, thereby implementing scanning. Because of the forward movement of the aircraft, the multispectral scanner accomplishes two-dimensional scanning, surface features and scenes are scanned point by point, and measurement is performed point by point in different bands, thereby obtaining multispectral remote sensing image information. The multispectral scanner is suitable for non-real-time detection of a static target, and is inapplicable to a moving target. The Fourier transform infrared imaging spectrometer can provide abundant two-dimensional space information and third-dimensional spectral data, that is, spectrum information may be extracted from each point for two-dimensional space imaging. In this device, image detection and spectrum detection share the same sensor, the amount of information for signal processing is very large, and high spatial resolution and high temporal resolution cannot be achieved at the same time; moreover, it is very expensive and a user cannot afford it.
In many actual applications, it is unnecessary to acquire spectrums of a static surface feature and a sky background in real time, but it is necessary to perform automatic and real-time detection identification on a moving target or a time-varying object (a local area) in a scene by using spectrum characteristics, for example, a flying aircraft, a ship on the sea, a traveling vehicle, a fire, an explosion, and the like.
An existing principled sample machine of an “image-spectrum integrated device” can implement automatic detection and spectrum identification of multiple moving objects and time-varying objects, but it has the following problems: (1) the device can merely acquire a spectrum of a medium-wave band (2 μm˜5 μm), while spectrum features of normal-temperature and low-temperature targets are mainly located in the long-wave band (8 μm˜14 μm), so that the device cannot perform effective detection on such targets; (2) the device measures infrared images and spectrums for targets of interest in the FOV, and also measures spectrum and performs spectrum feature identification on a target that can be effectively detected and identified by merely using an infrared image, thereby reducing the detection and identification efficiency; (3) the device uses a step-scan tracking mirror, so the tracking precision is relatively low; and (4) the device adopts an infrared window to effectively protect internal optical components; however, for use requirements of detection on a conventional target of a static platform having a good test condition, it is unnecessary to use the infrared window, so as to reduce the cost.